Evaluation of downscaling methods over Europe: Results of the EU‐COST action VALUE

Jack, Christopher; Katragkou, Eleni

doi:10.1002/joc.6184

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…However, RCMs and SD are dependent on the realism of the driving GCM and it is not always clear under what conditions RCMs improve the realism of the climate simulation (Dosio et al 2019). Among other limitations, SD methods also assume that observed climatological relationships will hold in the future warming world (statistical stationarity) which is not necessarily the case (Jack and Katragkou 2019). The added value or realism of regional modelling and SD is another area where multiple viewpoints are held, and expert judgement is deployed.…”

Section: Model Realismmentioning

confidence: 99%

Climate Information: Towards Transparent Distillation

Jack

Marsham

Rowell

et al. 2021

Climate Risk in Africa

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Constructing climate information to inform climate change risk-related decision-making is challenging and requires a rigorous interrogation and understanding of multiple lines of evidence and an assessment of the values, limits and uncertainties involved. Critically, there is no definitive approach agreed on by all climate scientists. Rather, a range of approaches and assumptions are used, with implications for robustness, reliability and uncertainty. Often these choices and assumptions are informed by the values and objectives of climate science rather than the decision context. We propose an approach, information distillation, that makes explicit and open for deliberation many of the implicit decisions and value judgements that occur throughout the process of constructing information. We argue that this approach must engage substantively with the decision context and open up choices and assumptions in a transparent manner to deliberation across climate scientists and context experts. This should ensure relevance and usability, and build understanding and trust to form an important basis for effective uptake of information. Two case studies are described demonstrating the effectiveness of these approaches and illustrating several important principles for transparent information distillation.

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Section: Model Realismmentioning

confidence: 99%

Climate Information: Towards Transparent Distillation

Jack

Marsham

Rowell

et al. 2021

Climate Risk in Africa

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“…Various GCM downscaling techniques have been developed to obtain projections in finer resolution for regional studies (Jack and Katragkou 2019) while some general challenges exist for their deployment in engineering (Karmalkar 2018;Lopez-Cantu et al 2020). The downscaled GCM projection products for the United States that practitioners can access include statistically downscaled products such as multivariate adaptive constructed analogs (MACA; Abatzoglou and Brown 2012), asynchronous regional regression model (Stoner et al 2013), and localized constructed analog (LOCA; Pierce et al 2014), as well as dynamically downscaled projection products [e.g., the North America-Coordinated Regional Downscaling Experiment (NA-CORDEX; Mearns et al 2017)] with applications of regional climate models (RCMs) including the recently developed convection-permitting RCMs (Prein et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation

Lai

Dzombak

2021

Journal of Applied Meteorology and Climatology

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An integrated technique combining global climate model (GCM) simulation results and a statistical time series forecasting model (the autoregressive integrated moving average ARIMA model) was developed to bring together the climate change signal from GCMs to city-level historical observations as an approach to obtain location-specific temperature and precipitation projections. This approach assumes that regional temperature and precipitation time series reflect a combination of an underlying climate change signal series and a regional-deviation-from-the-signal series. An ensemble of GCMs is used to describe and provide the climate change signal, and the ARIMA model is used to model and project the regional deviation. Qualitative and quantitative assessments were conducted for evaluating the projection performance of the hybrid GCM-ARIMA (G-ARIMA) model. The results indicate that the G-ARIMA model can provide projected city-specific daily temperature and precipitation series comparable to historical observations and can have improved projection accuracy for several assessed annual indices compared to a commonly used downscaled projection product. The G-ARIMA model is subject to some limitations and uncertainties from the GCM-provided climate change signal. A notable feature of the G-ARIMA model is the efficiency with which projections can be updated when new observations become available, thus facilitating updating of regional temperature and precipitations projections. Given the increasing need for and use of location-specific climate projections in practical engineering applications, the G-ARIMA model is an option for regional temperature and precipitation projection for such applications.

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Framing the Use of Climate Model Projections in Infrastructure Engineering: Practices, Uncertainties, and Recommendations

Lai

Lopez-Cantu

Dzombak

et al. 2022

J. Infrastruct. Syst.

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An overview of applying global climate model (GCM) projections of temperature and precipitation in infrastructure engineering is provided, with summarized general procedures, a review of commonly used projection products and processing techniques for different engineering applications, and sensitivity and uncertainty analyses with regard to different decisions via two case studies. Applying climate model projections in engineering requires multiple stages of decisions, which can be summarized as three steps: determining the requirements for climate variables, obtaining climate projections, and postprocessing of obtained climate projections. From the review of engineering applications in which climate projections were used, some important differences were identified during these three steps of decisions. The case studies suggested that the selections of projection products and processing techniques are subject to different kinds of uncertainty and challenges and that the sequence of decisions can lead to great variations in the resulting regional climate change projections. Based on the two case studies and the review of applications and uncertainties reported in the literature, several general observations and recommendations for applying GCM projections in engineering are offered.

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Evaluation of downscaling methods over Europe: Results of the EU‐COST action VALUE

Cited by 3 publications

References 28 publications

Climate Information: Towards Transparent Distillation

Climate Information: Towards Transparent Distillation

Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation

Framing the Use of Climate Model Projections in Infrastructure Engineering: Practices, Uncertainties, and Recommendations

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